类的目的就是根据现有的图像特征建立一个分类器，能够对未知的图像类型进行预测。在现有众多分类

算法中，贝叶斯分类器由于其坚实的数学理论基础并能综合先验信息和数据样本信息，成为"-3前机器学习和数据挖

掘的研究热点之一。本文论述了内容图像检索中基于贝叶斯分类器的图像分类技术。介绍了贝叶斯分类器，叙述了

利用贝叶斯分类器进行图像分类的方法，以及图像特征的分布假定。最后通过对分类器的探讨，总结了贝叶斯估计

分类的不足。-The purpose of class is based on an existing image features to create a classifier able to predict the unknown image type. Many of the existing classification algorithm, the Bayesian classifier because of its solid mathematical theory-based and comprehensive information prior information and data samples, a " -3 before the machine learning and data mining research focus of this paper discusses the Content-based Image Retrieval Bayesian classifier image classification techniques. introduced Bayesian classifier, described the use of Bayesian classifier for image classification methods, and the distribution of image features is assumed finally by classifier discussion summarizes the classification of the lack of Bayesian estimation.